Analysing multitrait-multimethod data with structural equation models for ordinal variables applying the WLSMV estimator: what sample size is needed for valid results?

Nussbeck FW, Eid M, Lischetzke T (2006)
The British journal of mathematical and statistical psychology 59(Pt 1): 195-213.

Journal Article | Published | English

No fulltext has been uploaded

Author
; ;
Abstract
Convergent and discriminant validity of psychological constructs can best be examined in the framework of multitrait-multimethod (MTMM) analysis. To gain information at the level of single items, MTMM models for categorical variables have to be applied. The CTC(M-1) model is presented as an example of an MTMM model for ordinal variables. Based on an empirical application of the CTC(M-1) model, a complex simulation study was conducted to examine the sample size requirements of the robust weighted least squares mean- and variance-adjusted chi(2) test of model fit (WLSMV estimator) implemented in Mplus. In particular, the simulation study analysed the chi(2) approximation, the parameter estimation bias, the standard error bias, and the reliability of the WLSMV estimator depending on the varying number of items per trait-method unit (ranging from 2 to 8) and varying sample sizes (250, 500, 750, and 1000 observations). The results showed that the WLSMV estimator provided a good -- albeit slightly liberal -- chi(2) approximation and stable and reliable parameter estimates for models of reasonable complexity (2-4 items) and small sample sizes (at least 250 observations). When more complex models with 5 or more items were analysed, larger sample sizes of at least 500 observations were needed. The most complex model with 9 trait-method units and 8 items (72 observed variables) requires sample sizes of at least 1000 observations.
Publishing Year
ISSN
PUB-ID

Cite this

Nussbeck FW, Eid M, Lischetzke T. Analysing multitrait-multimethod data with structural equation models for ordinal variables applying the WLSMV estimator: what sample size is needed for valid results? The British journal of mathematical and statistical psychology. 2006;59(Pt 1):195-213.
Nussbeck, F. W., Eid, M., & Lischetzke, T. (2006). Analysing multitrait-multimethod data with structural equation models for ordinal variables applying the WLSMV estimator: what sample size is needed for valid results? The British journal of mathematical and statistical psychology, 59(Pt 1), 195-213.
Nussbeck, F. W., Eid, M., and Lischetzke, T. (2006). Analysing multitrait-multimethod data with structural equation models for ordinal variables applying the WLSMV estimator: what sample size is needed for valid results? The British journal of mathematical and statistical psychology 59, 195-213.
Nussbeck, F.W., Eid, M., & Lischetzke, T., 2006. Analysing multitrait-multimethod data with structural equation models for ordinal variables applying the WLSMV estimator: what sample size is needed for valid results? The British journal of mathematical and statistical psychology, 59(Pt 1), p 195-213.
F.W. Nussbeck, M. Eid, and T. Lischetzke, “Analysing multitrait-multimethod data with structural equation models for ordinal variables applying the WLSMV estimator: what sample size is needed for valid results?”, The British journal of mathematical and statistical psychology, vol. 59, 2006, pp. 195-213.
Nussbeck, F.W., Eid, M., Lischetzke, T.: Analysing multitrait-multimethod data with structural equation models for ordinal variables applying the WLSMV estimator: what sample size is needed for valid results? The British journal of mathematical and statistical psychology. 59, 195-213 (2006).
Nussbeck, Fridtjof W., Eid, Michael, and Lischetzke, Tanja. “Analysing multitrait-multimethod data with structural equation models for ordinal variables applying the WLSMV estimator: what sample size is needed for valid results?”. The British journal of mathematical and statistical psychology 59.Pt 1 (2006): 195-213.
This data publication is cited in the following publications:
This publication cites the following data publications:

15 Citations in Europe PMC

Data provided by Europe PubMed Central.

Developing a comprehensive school connectedness scale for program evaluation.
Chung-Do JJ, Goebert DA, Chang JY, Hamagani F., J Sch Health 85(3), 2015
PMID: 25611940
CFA with binary variables in small samples: a comparison of two methods.
Savalei V, Bonett DG, Bentler PM., Front Psychol 5(), 2014
PMID: 25709585
Disinhibited eating and weight-related insulin mismanagement among individuals with type 1 diabetes.
Merwin RM, Moskovich AA, Dmitrieva NO, Pieper CF, Honeycutt LK, Zucker NL, Surwit RS, Buhi L., Appetite 81(), 2014
PMID: 24882448
A longitudinal multilevel CFA-MTMM model for interchangeable and structurally different methods.
Koch T, Schultze M, Eid M, Geiser C., Front Psychol 5(), 2014
PMID: 24860515
A trifactor model for integrating ratings across multiple informants.
Bauer DJ, Howard AL, Baldasaro RE, Curran PJ, Hussong AM, Chassin L, Zucker RA., Psychol Methods 18(4), 2013
PMID: 24079932
The validity of patient- and clinician-rated measures of needs and the therapeutic relationship in psychosis: a pooled analysis.
Reininghaus U, McCabe R, Slade M, Burns T, Croudace T, Priebe S., Psychiatry Res 209(3), 2013
PMID: 23452753
The performance of robust test statistics with categorical data.
Savalei V, Rhemtulla M., Br J Math Stat Psychol 66(2), 2013
PMID: 22568535
The structure of coping among older adults living with HIV/AIDS and depressive symptoms.
Hansen NB, Harrison B, Fambro S, Bodnar S, Heckman TG, Sikkema KJ., J Health Psychol 18(2), 2013
PMID: 22453164
The development and psychometric properties of the HIV and Abuse Related Shame Inventory (HARSI).
Neufeld SA, Sikkema KJ, Lee RS, Kochman A, Hansen NB., AIDS Behav 16(4), 2012
PMID: 22065235
Do executive and reactive disinhibition mediate the effects of familial substance use disorders on adolescent externalizing outcomes?
Handley ED, Chassin L, Haller MM, Bountress KE, Dandreaux D, Beltran I., J Abnorm Psychol 120(3), 2011
PMID: 21668077
Longitudinal associations between depressive and anxiety disorders: a comparison of two trait models.
Olino TM, Klein DN, Lewinsohn PM, Rohde P, Seeley JR., Psychol Med 38(3), 2008
PMID: 17803836

31 References

Data provided by Europe PubMed Central.

Convergent and discriminant validation by the multitrait-multimethod matrix.
CAMPBELL DT, FISKE DW., Psychol Bull 56(2), 1959
PMID: 13634291
Consensual validation of personality traits: Evidence from self-reports and ratings.
McCrae, Journal of Personality and Social Psychology 43(2), 1982

Eid, 2006
Confirmatory Factor Analyses of Multitrait-Multimethod Data: Many Problems and a Few Solutions
Marsh, Applied Psychological Measurement 13(4), 1989
Hierarchically Nested Covariance Structure Models for Multitrait-Multimethod Data
Widaman, Applied Psychological Measurement 9(1), 1985
Multitrait-multimethod Analysis
DUMENCI, 2000

Export

0 Marked Publications

Open Data PUB

Web of Science

View record in Web of Science®

Sources

PMID: 16709286
PubMed | Europe PMC

Search this title in

Google Scholar